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Provides a structured feature workflow with PRD/implementation planning, phased development, and document storage for LLM-driven coding features.
Configuration
View docs{
"mcpServers": {
"vibe_coder_mcp": {
"command": "/path/to/vibe-coder-mcp/build/mcp-server.js",
"args": []
}
}
}Vibe-Coder is a Model Context Protocol MCP server that guides LLM-based coding work through a structured feature clarification flow, PRD and implementation plan generation, phased development with task tracking, and built‑in document storage. It helps you organize feature work from concept to completion with clear progress reporting and accessible documents.
You use Vibe-Coder with an MCP client to plan, clarify, and track feature development. Start a feature clarification to gather requirements, then generate a PRD and implementation plan. Break the work into development phases and tasks, monitor progress, and keep feature documents stored and retrievable. Use the provided prompts and tools to guide questions, capture decisions, and store generated documents for later reference.
Typical usage flow: initiate a featureClarification to define intent and constraints, answer guided questions, request a PRD and implementation plan, create development phases, add tasks to each phase, and update statuses as work progresses. You can retrieve the location of generated documents and save copies to custom paths when needed.
Prerequisites: you need Node.js and npm installed on your machine. You also need a working MCP client that can connect to an MCP server via stdio.
Install dependencies for the MCP server project:
npm installBuild the server so it is ready to run in production or development environments:
npm run buildFor development with automatic rebuilds, you can watch for changes and rebuild automatically:
npm run watchConfiguration and storage are designed to be practical and transparent. Generated documents (PRDs and implementation plans) are automatically saved to disk and kept in memory for quick access. By default, documents live under documents/{featureId}/ with filenames based on the document type.
Default storage locations and filenames:
You can save documents to custom locations using the saveDocument operation, and you can retrieve a document’s path using getDocumentPath to verify where a file lives and whether it has been saved.
{
"featureId": "feature-123",
"documentType": "prd",
"filePath": "/custom/path/feature-123-prd.md"
}Debugging MCP servers can be challenging since they communicate over stdio. If you need debugging tools, use the MCP Inspector to access debugging utilities in your browser.
If you encounter issues during installation or runtime, verify you have the required Node.js version, check that dependencies install correctly, and ensure your development environment has access to the necessary file paths and permissions.
The MCP server can be connected to via a local stdio transport. Use a configuration that points to the built server for local runs.
{
"mcpServers": {
"vibe_coder_mcp": {
"type": "stdio",
"command": "/path/to/vibe-coder-mcp/build/mcp-server.js",
"args": []
}
}
}Begin the feature clarification process to collect requirements, target users, success criteria, constraints, and success metrics.
Answer clarification questions about a feature to refine its scope and requirements.
Generate a Product Requirements Document that captures the clarified feature details and acceptance criteria.
Create a development phase for a feature to organize work into logical stages with clear goals.
Add specific tasks to a development phase to break work into actionable steps.
Update the status of a development phase as work progresses.
Update the completion status of individual tasks.
Get guidance on what to do next in the workflow based on current progress.
Get the path of a generated document and whether it has been saved to disk.
Save a generated document to a specified location.